This research proposes to develop improved methods of calculating inverse solutions for the electrical activity in the heart. These solutions are obtained using electric potentials and magnetic fields measured at the surface of the body. Accurate inverse solutions would provide detailed information that would be of great value in the diagnosis and treatment of heart disease. Present methods of obtaining inverse solutions are not adequate to provide this information; they are too sensitive to the noise and modeling errors that exist under clinical conditions. Modeling errors are caused by differences between the actual source in the heart and some assumed model of it such as multiple dipole model. Modeling errors are also caused by the differences between the actual torso and some model of it. Three ways of developing improving methods would be investigated. The first would be to identify and eliminate or minimize the factors that cause noise and modeling errors to produce inaccurate solutions for multiple dipole heart models. This would be done using computer models of the heart and torso in which various parameters, such as dipole spacing and locations, surface measurement site locations, etc., could be varied to evaluate the effects of these parameters. The second way of developing improved methods is to use an assumed model that contains a number of multipole expansions. Previous research has shown that when one expansion is used as the assumed source, the lowest order terms, i.e., the dipole terms, are accurately obtained while the higher order terms are inaccurate. An assumed source which contains several multipole expansions should have accurate solutions for dipole terms in each expansion; the higher order terms will absorb the errors in the solution produced by noise and modeling errors. The third way of developing improved methods is to use magnetic or a combination of electric and magnetic data. Previous research has shown that electric and magnetic data can provide different information about the actual source inside a body when certain simple modeling errors are present. It is proposed to investigate improvements when realistic modeling errors are present.